A Novel ROS2 QoS Policy-Enabled Synchronizing Middleware for Co-Simulation of Heterogeneous Multi-Robot Systems

Recent Internet-of-Things (IoT) networks span across a multitude of stationary and robotic devices, namely unmanned ground vehicles, surface vessels, and aerial drones, to carry out mission-critical services such as search and rescue operations, wildfire monitoring, and flood/hurricane impact assessment. Achieving communication synchrony, reliability, and minimal communication jitter among these devices is a key challenge both at the simulation and system levels of implementation due to the underpinning differences between a physics-based robot operating system (ROS) simulator that is time-based and a network-based wireless simulator that is event-based, in addition to the complex dynamics of mobile and heterogeneous IoT devices deployed in a real environment. Nevertheless, synchronization between physics (robotics) and network simulators is one of the most difficult issues to address in simulating a heterogeneous multi-robot system before transitioning it into practice. The existing TCP/IP communication protocol-based synchronizing middleware mostly relied on Robot Operating System 1 (ROS1), which expends a significant portion of communication bandwidth and time due to its master-based architecture. To address these issues, we design a novel synchronizing middleware between robotics and traditional wireless network simulators, relying on the newly released real-time ROS2 architecture with a masterless packet discovery mechanism. Additionally, we propose a ground and aerial agents' velocity-aware customized QoS policy for Data Distribution Service (DDS) to minimize the packet loss and transmission latency between a diverse set of robotic agents, and we offer the theoretical guarantee of our proposed QoS policy. We performed extensive network performance evaluations both at the simulation and system levels in terms of packet loss probability and average latency with line-of-sight (LOS) and non-line-of-sight (NLOS) and TCP/UDP communication protocols over our proposed ROS2-based synchronization middleware. Moreover, for a comparative study, we presented a detailed ablation study replacing NS-3 with a real-time wireless network simulator, EMANE, and masterless ROS2 with master-based ROS1. Our proposed middleware attests to the promise of building a large-scale IoT infrastructure with a diverse set of stationary and robotic devices that achieve low-latency communications (12% and 11% reduction in simulation and reality, respectively) while satisfying the reliability (10% and 15% packet loss reduction in simulation and reality, respectively) and high-fidelity requirements of mission-critical applications.